Sorry I Made You Cry

This past week, I made two people cry.

The first was a nonprofit executive who had spent twenty-three years building a career she loved. A career known for building community and deep relationships. We were sitting in a green room before a conference session, the kind of windowless holding cell where speakers wait with bad coffee and good intentions. She had come to hear me talk about AI in the sector, but before I could start she told me, quietly, that she had been lying awake at night wondering if everything she had built was about to become irrelevant. She didn’t use the word “scared.” She used the word “stuck.” But her eyes told a different story.

The second was an entrepreneur I had known for a while. He had been aware of AI - had dabbled with the free version of ChatGPT for the past year, the way a lot of people have, tossing it a question here and there without ever really leaning in. I invited him to my home where we sat down together for a few hours, and I walked him through some basics in Claude Cowork and NotebookLM all the time using Wispr to dictate his voice while I asked him to describe the things he does every day that has made him successful for several decades. It wasn’t clean, organized or sexy prompting, it was garbled rhetoric and ideation, the way that you talk to a friend about a half lucid dream you had last night. Somewhere around the forty-five minute mark, his eyes went glassy. He wasn’t sad. He was overwhelmed in the other direction. This was a man with a head full of ideas he had never been able to execute - not for lack of ambition, but for lack of bandwidth. And suddenly, in one afternoon, a dozen of those ideas went from theoretical to instantly plausible. He described it later as going from a world of black and white to seeing in high-definition color. The tears were relief. The tears were release. The tears were the sound of a dam breaking after years of buildup. He’d heard the rhetoric about “powerful AI” but never fully realized what that looked like. Until now.

Same week. Same technology. Same chemical compound of tears. Two completely different reasons. One based in overwhelm, the other of exhilaration.

I tell you this not because I enjoy making people emotional, but because I think those two moments capture something that almost no one is talking about honestly. The conversation about artificial intelligence has been hijacked by two competing narratives, and both of them are failing us. One says AI will save everything. The other says AI will destroy everything. And in the space between those extremes, millions of thoughtful, capable people are sitting with a feeling they can barely name - a heaviness in the chest, a low hum of anxiety, a sense that the world is rearranging itself and nobody handed them the new blueprint.

If you recognize that feeling, this message is for you. Not because I have all the answers. But because I have been living inside this question since 2017, and I think the honest version of this conversation is overdue.

The Weight of the Room

On any given week, I receive five to six speaking requests - a number that has been steadily increasing over the past twenty-four months. The audiences vary - healthcare systems, higher education, faith-based organizations, foundations, Fortune 500 companies. The sectors differ. The titles in the room differ. But the energy is almost always the same. It carries a particular frequency, somewhere between curiosity and dread, and it fills the room before anyone says a word. A secret hope that I’ll tell everyone they should go home and do things the same way they’ve always done them. But my role is not to lure people into the comfort of what was, but instead to strike a sense of discomfort that enacts curiosity with urgency.

Unsurprisingly, the questions, when they come, tend to orbit the same center of gravity: What does this mean for me? Is my job safe? How do I succeed in a world I didn’t sign up for? If I’m a leader, how do I lead when the ground keeps shifting? How do I measure success when the goal posts keep shifting? And underneath all of those, the question no one asks out loud, but everyone is thinking: How much do I actually need to know?

These are not idle questions. They are not the musings of people who have too much time on their hands. They are the questions of people who have suddenly realized that the future they were planning for may not be the future that is arriving.

The data confirms what I see in those rooms. The American Psychological Association’s Stress in America 2025 survey found that fifty-seven percent of U.S. adults now cite the rise of AI as a significant source of stress - up from forty-nine percent just one year earlier. Among younger adults aged eighteen to thirty-four, that figure climbs to sixty-five percent. The stress is not abstract. It is not philosophical. It is the kind that disrupts sleep, strains relationships, and sits in the background of every workday like a weather system that never quite breaks.

A 2025 Pew Research Center survey found that American workers are more worried than hopeful about AI’s future role in the workplace, with fifty-two percent expressing concern compared to thirty-six percent expressing optimism. A third of workers believe AI will reduce the number of available jobs. Only six percent believe it will create more.

These numbers don’t describe a workforce that is resisting change out of stubbornness. They describe a workforce that is processing a profound shift in the meaning of competence, and doing so largely without support.

What We’re Really Afraid Of

A recent piece in the Harvard Business Review by Erik Hermann, Stefano Puntoni, and Carey Morewedge offers one of the most precise diagnoses I’ve seen of why AI feels so threatening. Their research identifies three psychological needs that generative AI disrupts: competence, the feeling of being effective and capable; autonomy, the feeling of being in control of one’s actions; and relatedness, the feeling of having meaningful connections to other people.

When a machine can draft what you draft, analyze what you analyze, and communicate what you communicate - often faster and without effort or complaint - it doesn’t just threaten your task list. It threatens your sense of self. The question stops being “Can I do this job?” and becomes “Am I still the person I thought I was?”

This is why the AI conversation so often feels like a conversation about identity masquerading as a conversation about technology. And it is why the standard corporate response - “Here’s a new tool, go take a training” - so often misses the mark. You cannot train your way out of an identity crisis. You have to walk through it.

The same Harvard Business Review research team proposes what they call the AWARE framework for leaders: acknowledge employee concerns, watch for adaptive and maladaptive coping, align support with psychological needs, redesign workflows around human-AI synergies, and empower workers through transparency. It is a useful framework. But frameworks alone are not what people need when they are awake at three in the morning staring at the ceiling. What they need first is someone to say: What you are feeling is rational. You are not behind. You are not broken. You are awake.

The Paradox Nobody Warned You About

Here is something that should trouble us more than it does. A separate study published in Harvard Business Review in early 2026, based on eight months of embedded research at a two-hundred-person technology company, found that AI tools did not reduce work. They intensified it.

Workers who adopted AI began operating at a faster pace, taking on a broader scope of tasks, and extending their work into more hours of the day - often without being asked. The researchers, Aruna Ranganathan and Xingqi Maggie Ye at UC Berkeley’s Haas School of Business, describe a self-reinforcing cycle: AI makes tasks easier, so workers take on more tasks, which increases their dependence on AI, which makes more tasks feel possible, which leads to more work. The promised efficiency gains quietly transformed into what the researchers call “workload creep.”

The implications are significant and largely ignored but should not be surprising. Did the invention of email afford us to work less? What looks like productivity in the short run can mask cognitive fatigue, weakened decision-making, and a growing inability to step away from work. Boundaries between work and rest dissolve not because the employer demands it, but because the technology makes overwork feel frictionless and even rewarding.

A separate DHR Global survey of 1,500 corporate professionals found eighty-three percent experiencing burnout, with overwhelming workloads and excessive hours as the leading contributors. The burnout gap by seniority is stark: sixty-two percent of associates and entry-level workers report burnout, compared with thirty-eight percent among C-suite leaders.

So the people with the least power and the least context are bearing the heaviest load. That should sound familiar to anyone who has worked in the nonprofit sector, where burnout has been a structural feature for decades. Now AI is adding a new layer: the anxiety of adaptation stacked on top of the exhaustion of execution.

The Signals Were Always There

I want to be honest about something that is uncomfortable to say. For those of us who have worked in AI for years, the current moment is not a surprise. It is the arrival of something we could see forming on the horizon for a long time. The World Economic Forum’s Future of Jobs Report projects that 170 million new roles will be created and 92 million displaced between 2025 and 2030 - a net gain of 78 million jobs. But that framing, while accurate, obscures the human reality underneath the numbers. The new jobs are not one-to-one swaps. They do not appear in the same industries, the same cities, or for the same people.

Forty percent of employers surveyed by the WEF plan to reduce their workforce where AI can automate tasks. Two-thirds plan to hire specifically for AI skills. And thirty-nine percent of core job skills are expected to change by 2030. These are not incremental shifts. They are structural transformations with a five-year runway. But change won’t wait five years to arrive. Speaking about this topic informally with Ben Greene, CRO of charity: water, last week, he shared that charity: water proactively assesses AI fluency and curiosity as a core job requirement when interviewing candidates.

Yet for the majority of people I speak with, this reality is still landing with a thud. The signals were there - in the steady improvement of language models, in the quiet automation of back-office functions, in the migration of knowledge work from human hands to machine prompts and headline stories on 60 Minutes. But the gravity of signals are easy to miss when your day is full. When your inbox is overflowing and no sense of slowing. When the next quarter’s numbers demand your full attention. Most people were not ignoring AI. They were just living their lives in a world that seemingly moves faster and faster. And then one morning they woke up to the realization that the world had rearranged itself while they were busy.

I don’t say this with judgment. I say it with empathy. Because I remember the moment it clicked for me, back in 2017, when I first began working with predictive AI in fundraising and realized that the technology wasn’t going to supplement what we did. It was going to redefine what “doing” meant. It would effectively resolve 2,300-year-old musings from Aristotle that explained why fundraising was hard. That realization didn’t arrive as excitement. It arrived as vertigo. And vertigo, I have come to learn, is the honest starting point for almost everyone who takes this seriously.

The Kindness Trap

There is a form of comfort that does real damage, and it is everywhere right now.

It sounds like: “Don’t worry, AI is overhyped.” It sounds like: “Your field is different, it won’t hit you.” It sounds like: “You’re smart, just keep doing what you’re doing.”

People say these things because they love you. Or because they love the version of the world that made them feel competent. Or because they are scared. But telling someone things will be fine while the landscape beneath them is shifting is not kindness. It is avoidance in a nice outfit.

If nothing else, humans are adaptable. Before the Industrial Revolution, roughly eighty percent of the world’s population worked in agriculture. Today, less than two percent do. We adapted. But that adaptation unfolded across generations. AI is not about slow, steady transformation. It is evolution on a hockey-stick curve. The World Economic Forum recently published a paper describing four possible futures for jobs by 2030. In the most optimistic scenario, exponential AI advancement meets a workforce that is broadly prepared - and even then, social safety nets and governance frameworks struggle to keep pace. In the worst case, which they call “The Age of Displacement,” AI advancement outpaces the workforce’s ability to adapt, economies fracture socially, unemployment spikes, and consumer confidence erodes.

We are not living in either extreme right now. We are living in the space between them, where the outcome is still being determined by what leaders, organizations, and individuals choose to do in the next few years. A middle moment filled with promise and opportunity for those who seek it. That is the honest framing. Not doom. Not hype. But urgency - the kind that respects people enough to tell them the truth.

A plan is built for a future you can predict. Adaptation is built for a future you can’t. If your strategy is conservation, you may be protecting today at the cost of tomorrow.

What I’ve Learned from the Rooms

After hundreds of keynotes, workshops, and late-night conversations in conference hallways, I have noticed a few patterns that I think are worth naming.

The fear is almost never about the technology itself. People are not lying awake worrying about large language models or transformer architectures. They are worried about relevance. About whether the story they have been telling themselves about their career, their expertise, their value still holds. AI didn’t create that vulnerability. But it put a spotlight on it that is impossible to ignore.

The people who adapt fastest are not the most technical. They are the most curious with haste. The 2026 Nonprofit AI Adoption Report from Virtuous and Fundraising.AI, a benchmark study of 346 organizations, shows that ninety-two percent of U.S. nonprofit professionals now use AI at work at least occasionally, but those reporting major improvements in organizational capability number just seven percent. The gap between those who are experimenting and those who are waiting is widening. And the differentiator is rarely technical skill. It is a posture of curiosity - a willingness to ask “What if?” instead of “What’s the point?”

Leaders are not immune. In fact, many of the most anxious people I meet are senior leaders who feel pressure to have answers they don’t yet have. A Gallup survey found that twenty-six percent of individual contributors didn’t even know whether their organization had officially adopted AI. The uncertainty runs from the bottom of the org chart to the top - it just expresses itself differently. At the individual level, it sounds like “Is my job safe?” At the leadership level, it sounds like “How fast is fast enough?”, “How do I measure success?” and, “Is my leadership style still relevant?”

The real question underneath every question is the same: “Do I still matter?” And the answer - the honest, research-backed, deeply human answer - is a declarative yes. But mattering in the age of AI requires a different kind of effort than mattering in the age before it. Sitting on the sidelines or assuming the way you’ve been doing things is the best or only way will not position you for a future of success.

The Case for Optimism (That Isn’t Naive)

I am an optimist. I believe in the power of “we.” Without that it would be difficult to get out of bed in the morning. But I am not the kind who pretends the storm isn’t real. I am the kind who believes that human beings, when given honest information and genuine support, are remarkably good at adapting. We have done it before. We will do it again. The question is whether we do it together or whether we let millions of people face this transition alone.

Here is what gives me genuine hope.

The World Economic Forum projects a net gain of 78 million jobs by 2030. The most in-demand skills are not coding or machine learning. They are analytical thinking, resilience, flexibility, leadership, and social influence. The skills that make us human - the ability to build trust, to make judgment calls in ambiguous situations, to inspire and connect - are not being automated. They are becoming more valuable.

PwC’s 2025 Global Workforce survey of nearly fifty thousand workers found that optimism about AI’s potential significantly outweighs anxiety for those who have actually begun using the tools. The gap between fear and engagement is often just one step: a single meaningful experience with AI that reveals it as a collaborator rather than a replacement. The engineering student who enters university terrified that AI will make everyone unemployable leaves a career fair reassured when a recruiter tells him the truth - that AI is making new hires dramatically more productive and that the company is excited about growth.

That is the story I see playing out in room after room. Fear yields to curiosity. Curiosity yields to experimentation. Experimentation fosters competence. And competence yields to something that looks a lot like empowerment.

The entrepreneur who cried in my presence last week wasn’t crying because AI solved his problems. He was crying because, for the first time, the scales had been removed from his eyes to realize the ideas he had been carrying around for years - ideas he had resigned himself to never building - suddenly had a path to reality. One afternoon with the right tools and someone willing to sit beside him and explore and challenge to play with AI for one hour a day, every day. That was all it took. The technology didn’t hand him a new life. It showed him the life he had been imagining was no longer out of reach.

What This Moment Asks of Us

If you are a leader, this moment asks you to be honest before you are strategic. Your people don’t need a polished AI roadmap as much as they need to hear you say: “I don’t have all the answers either, but I’m committed to figuring this out with you.” Trust is not built by having a plan. It is built by having the courage to name what you don’t know.

If you are a professional in any field, this moment asks you to get curious before you get comfortable. You don’t need to become a technologist. You need to become a learner. Start small. Try one tool. Ask one question. Have one conversation with someone who is already experimenting. The distance between paralysis and momentum is often a single afternoon of honest exploration.

If you are someone who is afraid, this moment asks you to let the fear be a signal, not a stop sign. You are not behind. The majority of people are still figuring this out. Forty percent of organizations don’t even have an official stance on AI. You are not late. You are at the beginning, and beginnings are supposed to feel uncertain.

And if you are someone like me - someone who works in AI and speaks about it publicly - this moment asks you to stop performing certainty. The world does not need more AI “experts” who pretend to have all the answers. It needs people who are willing to sit in the complexity, to name the tension between opportunity and loss, and to hold space for both the tears of overwhelm and the tears of possibility.

Sorry I Made You Cry

I’ve thought about those two conversations from last week more than I probably should have. The nonprofit executive who felt stuck and the entrepreneur who suddenly saw in color. Same technology. Same moment in history. Two different relationships with what is possible.

The difference between them was not technical literacy. It was not age or title or budget. The difference was proximity to the experience. One had been circling AI from a distance, absorbing headlines and secondhand anxiety. The other sat down for an afternoon, took a deep breath, got his hands on the tools, and let himself be surprised. That was it. That was the whole distance between dread and possibility - a few hours and a willingness to play.

I did not set out to make either of them cry. But I have stopped apologizing for telling the truth. Because I have come to believe that the most dangerous thing we can do in this moment is protect people from the reality of what is changing. Protection sounds compassionate. But it is often just a delay. And delays, in an exponential era, compound with interest.

The honest version of this conversation is harder. It acknowledges that some jobs will change beyond recognition. That some skills will lose their market value. That some of us will grieve the loss of a professional identity we spent decades building. That is real, and it deserves to be honored.

But the honest version also acknowledges that the human capacity for adaptation is extraordinary. That curiosity with urgency is not a luxury but a survival skill. That the people who thrive in what comes next will not be the ones who knew the most about AI, but the ones who knew the most about themselves - who understood what they valued, what they were willing to learn, and what kind of future they wanted to help build.

The American Psychological Association’s stress survey, for all its sobering findings, contains a quiet revelation: eighty-four percent of Americans still believe they can build a good life, and seventy-three percent believe they can help shape the country’s future for the better. That is not delusion. That is resilience. And it is the raw material from which every meaningful adaptation in human history has been built.

So no, I’m not sorry I made you cry. I’m sorry it took this long for someone to say it out loud. And I’m grateful - deeply, personally grateful - that you’re still here. Still reading. Still asking what comes next .

That question is the beginning of everything.

About the Author

Nathan Chappell, MBA, MNA, CFRE, AIGP is Chief AI Officer at Virtuous, co-author of Nonprofit AI and The Generosity Crisis. He writes about responsible innovation, the future of generosity, and the power of radical connection in the age of AI.